Table 8 Coefficients of the Q R ,Q W and LS μ LS regression for buffalo snowfall example
Ï„ | Weight | \(\widehat {\beta }_{0}{ (\tau)}\) | \(\widehat {\beta }_{1}{ (\tau)}\) | \(\widehat {\beta }_{2}{(\tau)}\) |
|---|---|---|---|---|
LS | − | 11.5280 | –0.1777 | 0.0053 |
0.95 | Q R | 25.7589 | –10.1068 | –0.0117 |
|  | Q W | 24.6887 | –0.6538 | 0.0315 |
0.96 | Q R | 28.7869 | 0.1543 | 0.0610 |
|  | Q W | 24.8614 | –0.7200 | 0.0352 |
0.97 | Q R | 30.7341 | 0.1488 | 0.0395 |
| Â | Q W | 28.5776 | 0.0551 | 0.0739 |
0.98 | Q R | 35.5582 | –0.2039 | 0.0223 |
|  | Q W | 25.8718 | –2.6593 | 0.3937 |
0.99 | Q R | 57.8614 | –2.6793 | 0.0330 |
| Â | Q R | 48.5464 | 0.5261 | 0.4768 |